{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Step 3: Pattern Confirmation\n",
    "\n",
    "1. [Analysis 1: Specificty and Concreteness](#a1)\n",
    "    2. [Measuring Specificity using WordNet](#spec)\n",
    "    2. [Measuring Concreteness using a Crowdsourced Weighted Dictionary](#concrete)<br><br> \n",
    "3. [Analysis 2: Counting People and Organizations Mentioned using Named Entity Recognition](#ner)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='a1'></a>\n",
    "# Analysis 1: Specificty and Concreteness"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas\n",
    "import nltk\n",
    "from nltk import word_tokenize\n",
    "from nltk.corpus import wordnet as wn\n",
    "from nltk.corpus import stopwords\n",
    "import numpy as np\n",
    "import scipy\n",
    "import matplotlib.pyplot as plt\n",
    "import json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Define function to count the number of hypernyms for each noun and verb\n",
    "def specificty(x):\n",
    "    x = x.replace('[\\x00-\\x1f]',\" \")\n",
    "    text = word_tokenize(x)\n",
    "    total_list = []\n",
    "    for w in text:\n",
    "        if not wn.synsets(w):\n",
    "            pass\n",
    "        else:\n",
    "            synset = wn.synsets(w)\n",
    "            #limit to nouns and verbs, as other words are not arranged hierarchically\n",
    "            if ((synset[0].pos() == (wn.NOUN)) or (synset[0].pos() == (wn.VERB))):\n",
    "                #I assume the most popular definition of each word.\n",
    "                paths = synset[0].hypernym_paths()\n",
    "                a_path = []\n",
    "                for num in range(0,len(paths)):\n",
    "                    a_path.append(len([synset.name for synset in paths[num]]))\n",
    "                    #I am taking the path with the minimum number of hypernyms, but this could be calculated some other way.\n",
    "                    path_num = min(a_path)\n",
    "                total_list.append( (w, path_num) )\n",
    "    return total_list\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Function to calculate the concreteness of a word based on the crowdsourced dictionary\n",
    "def concrete(x, dict):\n",
    "    x = x.replace('[\\x00-\\x1f]',\" \")\n",
    "    x = x.lower()\n",
    "    text = word_tokenize(x)\n",
    "    text = [word for word in text if word not in stopwords.words('english')]\n",
    "    concrete_score = []\n",
    "    for w in text:\n",
    "        if w in dict:\n",
    "            concrete_score.append((w, dict[w]))\n",
    "    return concrete_score"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create Strings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#first create strings for the two comparison texts,\n",
    "#Kant's The Metaphysical Elements of Ethics\n",
    "#and the Wikipedia page on Germany\n",
    "\n",
    "kant_string = open(\"../input_data/kant_metaphysics.txt\", 'r', encoding='utf-8').read()\n",
    "wiki_string = open(\"../input_data/wiki_germany.txt\", 'r', encoding='utf-8').read()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
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       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>25</td>\n",
       "      <td>chicago.cwlu_womankind.1973.02.15.txt</td>\n",
       "      <td>chicago</td>\n",
       "      <td>cwlu_womankind</td>\n",
       "      <td>1973</td>\n",
       "      <td>854</td>\n",
       "      <td>cwlu</td>\n",
       "      <td>26</td>\n",
       "      <td>2</td>\n",
       "      <td>1 18611939 1880s 1902 1902 1904 1906 1915 1915...</td>\n",
       "      <td>CWLU</td>\n",
       "      <td>15</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>26</td>\n",
       "      <td>nyc.redstockings.1973.willis.conservatismofms-...</td>\n",
       "      <td>nyc</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>1973</td>\n",
       "      <td>1154</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "      <td>171 1970 A Alpert Alpert Alpert Alpert Alperts...</td>\n",
       "      <td>willis</td>\n",
       "      <td>02</td>\n",
       "      <td>conservatismofms</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>27</td>\n",
       "      <td>nyc.redstockings.1973.serre.psychologique-4.txt</td>\n",
       "      <td>nyc</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>1973</td>\n",
       "      <td>318</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>28</td>\n",
       "      <td>2</td>\n",
       "      <td>1 197 1971 20 3 3 5 65 And As Be Brule But Fem...</td>\n",
       "      <td>serre</td>\n",
       "      <td>04</td>\n",
       "      <td>psychologique</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>28</td>\n",
       "      <td>chicago.hullhouse_bulletin.1916.01.60_article.txt</td>\n",
       "      <td>chicago</td>\n",
       "      <td>hullhouse_bulletin</td>\n",
       "      <td>1916</td>\n",
       "      <td>699</td>\n",
       "      <td>hullhouse</td>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "      <td>12060 130 1915 30 A Advancement Art Associatio...</td>\n",
       "      <td>Hull House</td>\n",
       "      <td>60</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>29</td>\n",
       "      <td>chicago.hullhouse_bulletin.1916.01.43_article.txt</td>\n",
       "      <td>chicago</td>\n",
       "      <td>hullhouse_bulletin</td>\n",
       "      <td>1916</td>\n",
       "      <td>362</td>\n",
       "      <td>hullhouse</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "      <td>A A Al Augusta Beauty Bowen Bowen Childrens Ch...</td>\n",
       "      <td>Hull House</td>\n",
       "      <td>43</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>993</th>\n",
       "      <td>993</td>\n",
       "      <td>notessecondyear_8.txt</td>\n",
       "      <td>nyc</td>\n",
       "      <td>notessecondyear</td>\n",
       "      <td>1969</td>\n",
       "      <td>1023</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>994</td>\n",
       "      <td>2</td>\n",
       "      <td>A A American And And And Applicant But But But...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>08</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>994</th>\n",
       "      <td>994</td>\n",
       "      <td>chicago.hullhouse_bulletin.1906.09.47_article.txt</td>\n",
       "      <td>chicago</td>\n",
       "      <td>hullhouse_bulletin</td>\n",
       "      <td>1906</td>\n",
       "      <td>730</td>\n",
       "      <td>hullhouse</td>\n",
       "      <td>995</td>\n",
       "      <td>1</td>\n",
       "      <td>11 111 11th 1907 1907 19th 1st 5 5 7 7th 830 9...</td>\n",
       "      <td>Hull House</td>\n",
       "      <td>47</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>995</td>\n",
       "      <td>chicago.hullhouse_bulletin.1901.05.10_article.txt</td>\n",
       "      <td>chicago</td>\n",
       "      <td>hullhouse_bulletin</td>\n",
       "      <td>1901</td>\n",
       "      <td>451</td>\n",
       "      <td>hullhouse</td>\n",
       "      <td>996</td>\n",
       "      <td>1</td>\n",
       "      <td>A AND ARTS Afternoons And Arts Bohemian Buildi...</td>\n",
       "      <td>Hull House</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>996</td>\n",
       "      <td>nyc.masses_1914.03.07.txt</td>\n",
       "      <td>nyc</td>\n",
       "      <td>masses</td>\n",
       "      <td>1914</td>\n",
       "      <td>212</td>\n",
       "      <td>heterodoxy</td>\n",
       "      <td>997</td>\n",
       "      <td>1</td>\n",
       "      <td>600000 A A ARE Ahout All And B Being COMPARATI...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>07</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>997</td>\n",
       "      <td>chicago.hullhouse_bulletin.1913.01.28_article.txt</td>\n",
       "      <td>chicago</td>\n",
       "      <td>hullhouse_bulletin</td>\n",
       "      <td>1913</td>\n",
       "      <td>352</td>\n",
       "      <td>hullhouse</td>\n",
       "      <td>998</td>\n",
       "      <td>1</td>\n",
       "      <td>A An An An As At Balaleika Balaleika Balls Bow...</td>\n",
       "      <td>Hull House</td>\n",
       "      <td>28</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>998</td>\n",
       "      <td>chicago.cwlu_womankind.1972.03.17.txt</td>\n",
       "      <td>chicago</td>\n",
       "      <td>cwlu_womankind</td>\n",
       "      <td>1972</td>\n",
       "      <td>819</td>\n",
       "      <td>cwlu</td>\n",
       "      <td>999</td>\n",
       "      <td>2</td>\n",
       "      <td>13 6 A AFTER All And And And And Any BabysitAn...</td>\n",
       "      <td>CWLU</td>\n",
       "      <td>17</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>999</td>\n",
       "      <td>chicago.hullhouse_bulletin.1900.08.13_article.txt</td>\n",
       "      <td>chicago</td>\n",
       "      <td>hullhouse_bulletin</td>\n",
       "      <td>1900</td>\n",
       "      <td>908</td>\n",
       "      <td>hullhouse</td>\n",
       "      <td>1000</td>\n",
       "      <td>1</td>\n",
       "      <td>26th 7th 7th 7th AND Addams Association Associ...</td>\n",
       "      <td>Hull House</td>\n",
       "      <td>13</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1000</th>\n",
       "      <td>1000</td>\n",
       "      <td>nyc.redstockings.1973.brooke.sexroletheory-1.txt</td>\n",
       "      <td>nyc</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>1973</td>\n",
       "      <td>965</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>1001</td>\n",
       "      <td>2</td>\n",
       "      <td>According Although And Anne Are As Betty Blami...</td>\n",
       "      <td>brooke</td>\n",
       "      <td>01</td>\n",
       "      <td>sexroletheory</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1001</th>\n",
       "      <td>1001</td>\n",
       "      <td>nyc.redstockings.1973.price.keepingwomenout-05...</td>\n",
       "      <td>nyc</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>1973</td>\n",
       "      <td>261</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>1002</td>\n",
       "      <td>2</td>\n",
       "      <td>1 1000 1000 1010 1010 1020 1050 1900 1940 1960...</td>\n",
       "      <td>price</td>\n",
       "      <td>05</td>\n",
       "      <td>keepingwomenout</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1002</th>\n",
       "      <td>1002</td>\n",
       "      <td>chicago.cwlu_womankind.1972.07.12.txt</td>\n",
       "      <td>chicago</td>\n",
       "      <td>cwlu_womankind</td>\n",
       "      <td>1972</td>\n",
       "      <td>1748</td>\n",
       "      <td>cwlu</td>\n",
       "      <td>1003</td>\n",
       "      <td>2</td>\n",
       "      <td>1 10 10 14 15 15 16 1970 2 2 29 3 34 37270 4 4...</td>\n",
       "      <td>CWLU</td>\n",
       "      <td>12</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1003</th>\n",
       "      <td>1003</td>\n",
       "      <td>notessecondyear_43.txt</td>\n",
       "      <td>nyc</td>\n",
       "      <td>notessecondyear</td>\n",
       "      <td>1969</td>\n",
       "      <td>895</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>1004</td>\n",
       "      <td>2</td>\n",
       "      <td>10 A Adult As At Because Gradually He Hindu Hi...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1004</th>\n",
       "      <td>1004</td>\n",
       "      <td>nyc.masses_1915.11.08.txt</td>\n",
       "      <td>nyc</td>\n",
       "      <td>masses</td>\n",
       "      <td>1915</td>\n",
       "      <td>1372</td>\n",
       "      <td>heterodoxy</td>\n",
       "      <td>1005</td>\n",
       "      <td>1</td>\n",
       "      <td>And And And And Because But But Do For I I I I...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>08</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1005</th>\n",
       "      <td>1005</td>\n",
       "      <td>nyc.redstockings.1973.sarachild.powerofhistory...</td>\n",
       "      <td>nyc</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>1973</td>\n",
       "      <td>417</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>1006</td>\n",
       "      <td>2</td>\n",
       "      <td>1968 1970 1970 AND Above America Among Atlanti...</td>\n",
       "      <td>sarachild</td>\n",
       "      <td>05</td>\n",
       "      <td>powerofhistory</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1006</th>\n",
       "      <td>1006</td>\n",
       "      <td>chicago.cwlu_womankind.1972.03.03.txt</td>\n",
       "      <td>chicago</td>\n",
       "      <td>cwlu_womankind</td>\n",
       "      <td>1972</td>\n",
       "      <td>691</td>\n",
       "      <td>cwlu</td>\n",
       "      <td>1007</td>\n",
       "      <td>2</td>\n",
       "      <td>3 37 9 A Act And Association August British Bu...</td>\n",
       "      <td>CWLU</td>\n",
       "      <td>03</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1007</th>\n",
       "      <td>1007</td>\n",
       "      <td>nyc.redstockings.1973.leon.dirtytricks-03.txt</td>\n",
       "      <td>nyc</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>1973</td>\n",
       "      <td>1208</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>1008</td>\n",
       "      <td>2</td>\n",
       "      <td>15year 1953 1957 195960 195962 1965 1965 1967 ...</td>\n",
       "      <td>leon</td>\n",
       "      <td>03</td>\n",
       "      <td>dirtytricks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1008</th>\n",
       "      <td>1008</td>\n",
       "      <td>chicago.cwlu_womankind.1973.02.11.txt</td>\n",
       "      <td>chicago</td>\n",
       "      <td>cwlu_womankind</td>\n",
       "      <td>1973</td>\n",
       "      <td>1912</td>\n",
       "      <td>cwlu</td>\n",
       "      <td>1009</td>\n",
       "      <td>2</td>\n",
       "      <td>170 19 197172 1972 1972 1972 1972 1973 20 200 ...</td>\n",
       "      <td>CWLU</td>\n",
       "      <td>11</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1009</th>\n",
       "      <td>1009</td>\n",
       "      <td>nyc.redstockings.1973.sarachild.powerofhistory...</td>\n",
       "      <td>nyc</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>1973</td>\n",
       "      <td>1218</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>1010</td>\n",
       "      <td>2</td>\n",
       "      <td>100 1959 Anthony Anthony Anthony Anthony Antho...</td>\n",
       "      <td>sarachild</td>\n",
       "      <td>27</td>\n",
       "      <td>powerofhistory</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1010</th>\n",
       "      <td>1010</td>\n",
       "      <td>chicago.cwlu_womankind.1972.02.22.txt</td>\n",
       "      <td>chicago</td>\n",
       "      <td>cwlu_womankind</td>\n",
       "      <td>1972</td>\n",
       "      <td>599</td>\n",
       "      <td>cwlu</td>\n",
       "      <td>1011</td>\n",
       "      <td>2</td>\n",
       "      <td>100 12 1250 180 1910 1910 1969 1970 1970 2 2 2...</td>\n",
       "      <td>CWLU</td>\n",
       "      <td>22</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1011</th>\n",
       "      <td>1011</td>\n",
       "      <td>chicago.hullhouse_bulletin.1903.01.18_article.txt</td>\n",
       "      <td>chicago</td>\n",
       "      <td>hullhouse_bulletin</td>\n",
       "      <td>1903</td>\n",
       "      <td>750</td>\n",
       "      <td>hullhouse</td>\n",
       "      <td>1012</td>\n",
       "      <td>1</td>\n",
       "      <td>11 12 1903 5 7 8 9 A AJAX APARTMENTS Achilles ...</td>\n",
       "      <td>Hull House</td>\n",
       "      <td>18</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1012</th>\n",
       "      <td>1012</td>\n",
       "      <td>chicago.cwlu_womankind.1973.09.06.txt</td>\n",
       "      <td>chicago</td>\n",
       "      <td>cwlu_womankind</td>\n",
       "      <td>1973</td>\n",
       "      <td>1158</td>\n",
       "      <td>cwlu</td>\n",
       "      <td>1013</td>\n",
       "      <td>2</td>\n",
       "      <td>1000year 12 2 212 23 5000 60s Action Again Age...</td>\n",
       "      <td>CWLU</td>\n",
       "      <td>06</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1013</th>\n",
       "      <td>1013</td>\n",
       "      <td>chicago.cwlu_womankind.1972.07.01.txt</td>\n",
       "      <td>chicago</td>\n",
       "      <td>cwlu_womankind</td>\n",
       "      <td>1972</td>\n",
       "      <td>46</td>\n",
       "      <td>cwlu</td>\n",
       "      <td>1014</td>\n",
       "      <td>2</td>\n",
       "      <td>1 10 11 11 14 1972 25 8 Chicago JULY Liberatio...</td>\n",
       "      <td>CWLU</td>\n",
       "      <td>01</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1014</th>\n",
       "      <td>1014</td>\n",
       "      <td>nyc.redstockings.1973.price.keepingwomenout-11...</td>\n",
       "      <td>nyc</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>1973</td>\n",
       "      <td>815</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>1015</td>\n",
       "      <td>2</td>\n",
       "      <td>100000 10786 131 1380000year 1500000year 15000...</td>\n",
       "      <td>price</td>\n",
       "      <td>11</td>\n",
       "      <td>keepingwomenout</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1015</th>\n",
       "      <td>1015</td>\n",
       "      <td>notessecondyear_18.txt</td>\n",
       "      <td>nyc</td>\n",
       "      <td>notessecondyear</td>\n",
       "      <td>1969</td>\n",
       "      <td>1059</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>1016</td>\n",
       "      <td>2</td>\n",
       "      <td>2 And And But But But But For He His I I In In...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1016</th>\n",
       "      <td>1016</td>\n",
       "      <td>nyc.redstockings.1973.sarachild.powerofhistory...</td>\n",
       "      <td>nyc</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>1973</td>\n",
       "      <td>1142</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>1017</td>\n",
       "      <td>2</td>\n",
       "      <td>2 A A A A All And And And As As As As Because ...</td>\n",
       "      <td>sarachild</td>\n",
       "      <td>13</td>\n",
       "      <td>powerofhistory</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1017</th>\n",
       "      <td>1017</td>\n",
       "      <td>nyc.masses_1915.11.09.txt</td>\n",
       "      <td>nyc</td>\n",
       "      <td>masses</td>\n",
       "      <td>1915</td>\n",
       "      <td>1643</td>\n",
       "      <td>heterodoxy</td>\n",
       "      <td>1018</td>\n",
       "      <td>1</td>\n",
       "      <td>A A A A A A A Against Ah Alice All Allies And ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>09</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1018</th>\n",
       "      <td>1018</td>\n",
       "      <td>chicago.hullhouse_bulletin.1910.05.36_article.txt</td>\n",
       "      <td>chicago</td>\n",
       "      <td>hullhouse_bulletin</td>\n",
       "      <td>1910</td>\n",
       "      <td>270</td>\n",
       "      <td>hullhouse</td>\n",
       "      <td>1019</td>\n",
       "      <td>1</td>\n",
       "      <td>A Another Association Association Christmas Ch...</td>\n",
       "      <td>Hull House</td>\n",
       "      <td>36</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1019</th>\n",
       "      <td>1019</td>\n",
       "      <td>chicago.hullhouse_bulletin.1905.08.22_article.txt</td>\n",
       "      <td>chicago</td>\n",
       "      <td>hullhouse_bulletin</td>\n",
       "      <td>1905</td>\n",
       "      <td>845</td>\n",
       "      <td>hullhouse</td>\n",
       "      <td>1020</td>\n",
       "      <td>1</td>\n",
       "      <td>100 106 1101tionse 1896 1897 1c6 1st 43 A Aid ...</td>\n",
       "      <td>Hull House</td>\n",
       "      <td>22</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1020</th>\n",
       "      <td>1020</td>\n",
       "      <td>chicago.cwlu_womankind.1972.04.01.txt</td>\n",
       "      <td>chicago</td>\n",
       "      <td>cwlu_womankind</td>\n",
       "      <td>1972</td>\n",
       "      <td>20</td>\n",
       "      <td>cwlu</td>\n",
       "      <td>1021</td>\n",
       "      <td>2</td>\n",
       "      <td>1 1972 8 April Home Womankind and girls is no ...</td>\n",
       "      <td>CWLU</td>\n",
       "      <td>01</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1021</th>\n",
       "      <td>1021</td>\n",
       "      <td>chicago.cwlu_womankind.1971.12.14.txt</td>\n",
       "      <td>chicago</td>\n",
       "      <td>cwlu_womankind</td>\n",
       "      <td>1971</td>\n",
       "      <td>1195</td>\n",
       "      <td>cwlu</td>\n",
       "      <td>1022</td>\n",
       "      <td>2</td>\n",
       "      <td>95 Adn And And And Answering At At Because Bei...</td>\n",
       "      <td>CWLU</td>\n",
       "      <td>14</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1022</th>\n",
       "      <td>1022</td>\n",
       "      <td>nyc.redstockings.1973.leon.conditioningline-3.txt</td>\n",
       "      <td>nyc</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>1973</td>\n",
       "      <td>1119</td>\n",
       "      <td>redstockings</td>\n",
       "      <td>1023</td>\n",
       "      <td>2</td>\n",
       "      <td>1 1970 1971 2 3 4 5 6 A A A A According Aug Br...</td>\n",
       "      <td>leon</td>\n",
       "      <td>03</td>\n",
       "      <td>conditioningline</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1023 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Unnamed: 0.1                                                doc  \\\n",
       "0                0                             notessecondyear_70.txt   \n",
       "1                1              chicago.cwlu_womankind.1971.11.06.txt   \n",
       "2                2                          nyc.masses_1916.04.21.txt   \n",
       "3                3  nyc.redstockings.1973.mainardi.marriagequestio...   \n",
       "4                4              chicago.cwlu_womankind.1972.01.01.txt   \n",
       "5                5                              notesfirstyear_30.txt   \n",
       "6                6              chicago.cwlu_womankind.1972.05.14.txt   \n",
       "7                7  nyc.redstockings.1973.sarachild.programforcons...   \n",
       "8                8              chicago.cwlu_womankind.1972.11.11.txt   \n",
       "9                9              chicago.cwlu_womankind.1972.03.20.txt   \n",
       "10              10              chicago.cwlu_womankind.1972.01.12.txt   \n",
       "11              11              chicago.cwlu_womankind.1972.09.06.txt   \n",
       "12              12              chicago.cwlu_womankind.1973.04.16.txt   \n",
       "13              13              chicago.cwlu_womankind.1972.12.08.txt   \n",
       "14              14              chicago.cwlu_womankind.1973.11.06.txt   \n",
       "15              15              chicago.cwlu_womankind.1973.06.08.txt   \n",
       "16              16              chicago.cwlu_womankind.1972.06.13.txt   \n",
       "17              17              chicago.cwlu_womankind.1972.12.05.txt   \n",
       "18              18  nyc.redstockings.1973.hanisch.mensliberation-3...   \n",
       "19              19  nyc.redstockings.1973.hanisch.workingconscious...   \n",
       "20              20                             notessecondyear_25.txt   \n",
       "21              21  nyc.redstockings.1973.sarachild.whatwereallywa...   \n",
       "22              22              chicago.cwlu_womankind.1971.12.03.txt   \n",
       "23              23  chicago.hullhouse_bulletin.1916.01.61_article.txt   \n",
       "24              24              chicago.cwlu_womankind.1973.09.04.txt   \n",
       "25              25              chicago.cwlu_womankind.1973.02.15.txt   \n",
       "26              26  nyc.redstockings.1973.willis.conservatismofms-...   \n",
       "27              27    nyc.redstockings.1973.serre.psychologique-4.txt   \n",
       "28              28  chicago.hullhouse_bulletin.1916.01.60_article.txt   \n",
       "29              29  chicago.hullhouse_bulletin.1916.01.43_article.txt   \n",
       "...            ...                                                ...   \n",
       "993            993                              notessecondyear_8.txt   \n",
       "994            994  chicago.hullhouse_bulletin.1906.09.47_article.txt   \n",
       "995            995  chicago.hullhouse_bulletin.1901.05.10_article.txt   \n",
       "996            996                          nyc.masses_1914.03.07.txt   \n",
       "997            997  chicago.hullhouse_bulletin.1913.01.28_article.txt   \n",
       "998            998              chicago.cwlu_womankind.1972.03.17.txt   \n",
       "999            999  chicago.hullhouse_bulletin.1900.08.13_article.txt   \n",
       "1000          1000   nyc.redstockings.1973.brooke.sexroletheory-1.txt   \n",
       "1001          1001  nyc.redstockings.1973.price.keepingwomenout-05...   \n",
       "1002          1002              chicago.cwlu_womankind.1972.07.12.txt   \n",
       "1003          1003                             notessecondyear_43.txt   \n",
       "1004          1004                          nyc.masses_1915.11.08.txt   \n",
       "1005          1005  nyc.redstockings.1973.sarachild.powerofhistory...   \n",
       "1006          1006              chicago.cwlu_womankind.1972.03.03.txt   \n",
       "1007          1007      nyc.redstockings.1973.leon.dirtytricks-03.txt   \n",
       "1008          1008              chicago.cwlu_womankind.1973.02.11.txt   \n",
       "1009          1009  nyc.redstockings.1973.sarachild.powerofhistory...   \n",
       "1010          1010              chicago.cwlu_womankind.1972.02.22.txt   \n",
       "1011          1011  chicago.hullhouse_bulletin.1903.01.18_article.txt   \n",
       "1012          1012              chicago.cwlu_womankind.1973.09.06.txt   \n",
       "1013          1013              chicago.cwlu_womankind.1972.07.01.txt   \n",
       "1014          1014  nyc.redstockings.1973.price.keepingwomenout-11...   \n",
       "1015          1015                             notessecondyear_18.txt   \n",
       "1016          1016  nyc.redstockings.1973.sarachild.powerofhistory...   \n",
       "1017          1017                          nyc.masses_1915.11.09.txt   \n",
       "1018          1018  chicago.hullhouse_bulletin.1910.05.36_article.txt   \n",
       "1019          1019  chicago.hullhouse_bulletin.1905.08.22_article.txt   \n",
       "1020          1020              chicago.cwlu_womankind.1972.04.01.txt   \n",
       "1021          1021              chicago.cwlu_womankind.1971.12.14.txt   \n",
       "1022          1022  nyc.redstockings.1973.leon.conditioningline-3.txt   \n",
       "\n",
       "         city         publication  date  word_count           org  identifier  \\\n",
       "0         nyc     notessecondyear  1969         553  redstockings           1   \n",
       "1     chicago      cwlu_womankind  1971         890          cwlu           2   \n",
       "2         nyc              masses  1916         425    heterodoxy           3   \n",
       "3         nyc        redstockings  1973         972  redstockings           4   \n",
       "4     chicago      cwlu_womankind  1972          39          cwlu           5   \n",
       "5         nyc      notesfirstyear  1968         442  redstockings           6   \n",
       "6     chicago      cwlu_womankind  1972         976          cwlu           7   \n",
       "7         nyc        redstockings  1973         785  redstockings           8   \n",
       "8     chicago      cwlu_womankind  1972         985          cwlu           9   \n",
       "9     chicago      cwlu_womankind  1972         369          cwlu          10   \n",
       "10    chicago      cwlu_womankind  1972         938          cwlu          11   \n",
       "11    chicago      cwlu_womankind  1972        1591          cwlu          12   \n",
       "12    chicago      cwlu_womankind  1973         689          cwlu          13   \n",
       "13    chicago      cwlu_womankind  1972        1130          cwlu          14   \n",
       "14    chicago      cwlu_womankind  1973         899          cwlu          15   \n",
       "15    chicago      cwlu_womankind  1973        1106          cwlu          16   \n",
       "16    chicago      cwlu_womankind  1972        1573          cwlu          17   \n",
       "17    chicago      cwlu_womankind  1972        1439          cwlu          18   \n",
       "18        nyc        redstockings  1973        1094  redstockings          19   \n",
       "19        nyc        redstockings  1973        1011  redstockings          20   \n",
       "20        nyc     notessecondyear  1969         974  redstockings          21   \n",
       "21        nyc        redstockings  1973         959  redstockings          22   \n",
       "22    chicago      cwlu_womankind  1971         137          cwlu          23   \n",
       "23    chicago  hullhouse_bulletin  1916         717     hullhouse          24   \n",
       "24    chicago      cwlu_womankind  1973         878          cwlu          25   \n",
       "25    chicago      cwlu_womankind  1973         854          cwlu          26   \n",
       "26        nyc        redstockings  1973        1154  redstockings          27   \n",
       "27        nyc        redstockings  1973         318  redstockings          28   \n",
       "28    chicago  hullhouse_bulletin  1916         699     hullhouse          29   \n",
       "29    chicago  hullhouse_bulletin  1916         362     hullhouse          30   \n",
       "...       ...                 ...   ...         ...           ...         ...   \n",
       "993       nyc     notessecondyear  1969        1023  redstockings         994   \n",
       "994   chicago  hullhouse_bulletin  1906         730     hullhouse         995   \n",
       "995   chicago  hullhouse_bulletin  1901         451     hullhouse         996   \n",
       "996       nyc              masses  1914         212    heterodoxy         997   \n",
       "997   chicago  hullhouse_bulletin  1913         352     hullhouse         998   \n",
       "998   chicago      cwlu_womankind  1972         819          cwlu         999   \n",
       "999   chicago  hullhouse_bulletin  1900         908     hullhouse        1000   \n",
       "1000      nyc        redstockings  1973         965  redstockings        1001   \n",
       "1001      nyc        redstockings  1973         261  redstockings        1002   \n",
       "1002  chicago      cwlu_womankind  1972        1748          cwlu        1003   \n",
       "1003      nyc     notessecondyear  1969         895  redstockings        1004   \n",
       "1004      nyc              masses  1915        1372    heterodoxy        1005   \n",
       "1005      nyc        redstockings  1973         417  redstockings        1006   \n",
       "1006  chicago      cwlu_womankind  1972         691          cwlu        1007   \n",
       "1007      nyc        redstockings  1973        1208  redstockings        1008   \n",
       "1008  chicago      cwlu_womankind  1973        1912          cwlu        1009   \n",
       "1009      nyc        redstockings  1973        1218  redstockings        1010   \n",
       "1010  chicago      cwlu_womankind  1972         599          cwlu        1011   \n",
       "1011  chicago  hullhouse_bulletin  1903         750     hullhouse        1012   \n",
       "1012  chicago      cwlu_womankind  1973        1158          cwlu        1013   \n",
       "1013  chicago      cwlu_womankind  1972          46          cwlu        1014   \n",
       "1014      nyc        redstockings  1973         815  redstockings        1015   \n",
       "1015      nyc     notessecondyear  1969        1059  redstockings        1016   \n",
       "1016      nyc        redstockings  1973        1142  redstockings        1017   \n",
       "1017      nyc              masses  1915        1643    heterodoxy        1018   \n",
       "1018  chicago  hullhouse_bulletin  1910         270     hullhouse        1019   \n",
       "1019  chicago  hullhouse_bulletin  1905         845     hullhouse        1020   \n",
       "1020  chicago      cwlu_womankind  1972          20          cwlu        1021   \n",
       "1021  chicago      cwlu_womankind  1971        1195          cwlu        1022   \n",
       "1022      nyc        redstockings  1973        1119  redstockings        1023   \n",
       "\n",
       "      wave                                        text_string      author  \\\n",
       "0        2  1 1 1 1 1 10 11 2 2 2 2 3 3 3 4 5 6 7 8 9 A An...         NaN   \n",
       "1        2  411 93 Actually Alice American American Any As...        CWLU   \n",
       "2        1  All Anarchist Anarchist And Birth Birth Birth ...         NaN   \n",
       "3        2  1968 1968 50s 60s Although Although American A...    mainardi   \n",
       "4        2  1972 5 Ghots I January Womankind a bind by cro...        CWLU   \n",
       "5        2  12 12 15 1868 1868 1968 28 A AUNT All Anybody ...         NaN   \n",
       "6        2  1 1970 2 2 3 4 4 5 6 7 8 A AT Also Also Amer A...        CWLU   \n",
       "7        2  1 2 3 A A A APPENDIX And CONSCIOUSNESSRAISING ...   sarachild   \n",
       "8        2  1867 1972 A AND ARTICLES Adopt Affiar All Amaz...        CWLU   \n",
       "9        2  Above CWLU CWLU CWLU Chicago Chicago Discus Li...        CWLU   \n",
       "10       2  10 12volt 15 6volt 6volt 6volt A A Another As ...        CWLU   \n",
       "11       2  1930s 1930s 1auqhter 30s 5th 6th 7871786 A Act...        CWLU   \n",
       "12       2  25 29 2ND 4 656 A Any Any April As Barry But C...        CWLU   \n",
       "13       2  10 1020 1161 12 1300s 1500 1793 1930s 1950s 19...        CWLU   \n",
       "14       2  14 30 ABORTION AFLCIO AFLCIO AND Abortions Act...        CWLU   \n",
       "15       2  112940 1970 1971 1972 1972 1974 26000 3 341840...        CWLU   \n",
       "16       2  1 1100015000 13 13 1318 18 1800036000 1972 1eV...        CWLU   \n",
       "17       2  1972 2 2 3 4 438211 552 575 79 852 A A A A A A...        CWLU   \n",
       "18       2  1000 150 375 6 7 74 And Apparently As As Avenu...     hanisch   \n",
       "19       2  2 3 3 4 4 Although Being But Do Do FROM Gradua...     hanisch   \n",
       "20       2  1 1 1570 2 3 369 4 5 5 50 6 6 7 7 8 92169 95 A...         NaN   \n",
       "21       2  1971 26 All And And And And August Being But C...   sarachild   \n",
       "22       2  1970 A A AGGRESS ALL AND ANOTHER AS BE BEFORE ...        CWLU   \n",
       "23       1  1914 1915 Abbott Addams Addams Addams Aletta A...  Hull House   \n",
       "24       2  100000 10th 13 160 1950s 1972 1972 20hour 21 2...        CWLU   \n",
       "25       2  1 18611939 1880s 1902 1902 1904 1906 1915 1915...        CWLU   \n",
       "26       2  171 1970 A Alpert Alpert Alpert Alpert Alperts...      willis   \n",
       "27       2  1 197 1971 20 3 3 5 65 And As Be Brule But Fem...       serre   \n",
       "28       1  12060 130 1915 30 A Advancement Art Associatio...  Hull House   \n",
       "29       1  A A Al Augusta Beauty Bowen Bowen Childrens Ch...  Hull House   \n",
       "...    ...                                                ...         ...   \n",
       "993      2  A A American And And And Applicant But But But...         NaN   \n",
       "994      1  11 111 11th 1907 1907 19th 1st 5 5 7 7th 830 9...  Hull House   \n",
       "995      1  A AND ARTS Afternoons And Arts Bohemian Buildi...  Hull House   \n",
       "996      1  600000 A A ARE Ahout All And B Being COMPARATI...         NaN   \n",
       "997      1  A An An An As At Balaleika Balaleika Balls Bow...  Hull House   \n",
       "998      2  13 6 A AFTER All And And And And Any BabysitAn...        CWLU   \n",
       "999      1  26th 7th 7th 7th AND Addams Association Associ...  Hull House   \n",
       "1000     2  According Although And Anne Are As Betty Blami...      brooke   \n",
       "1001     2  1 1000 1000 1010 1010 1020 1050 1900 1940 1960...       price   \n",
       "1002     2  1 10 10 14 15 15 16 1970 2 2 29 3 34 37270 4 4...        CWLU   \n",
       "1003     2  10 A Adult As At Because Gradually He Hindu Hi...         NaN   \n",
       "1004     1  And And And And Because But But Do For I I I I...         NaN   \n",
       "1005     2  1968 1970 1970 AND Above America Among Atlanti...   sarachild   \n",
       "1006     2  3 37 9 A Act And Association August British Bu...        CWLU   \n",
       "1007     2  15year 1953 1957 195960 195962 1965 1965 1967 ...        leon   \n",
       "1008     2  170 19 197172 1972 1972 1972 1972 1973 20 200 ...        CWLU   \n",
       "1009     2  100 1959 Anthony Anthony Anthony Anthony Antho...   sarachild   \n",
       "1010     2  100 12 1250 180 1910 1910 1969 1970 1970 2 2 2...        CWLU   \n",
       "1011     1  11 12 1903 5 7 8 9 A AJAX APARTMENTS Achilles ...  Hull House   \n",
       "1012     2  1000year 12 2 212 23 5000 60s Action Again Age...        CWLU   \n",
       "1013     2  1 10 11 11 14 1972 25 8 Chicago JULY Liberatio...        CWLU   \n",
       "1014     2  100000 10786 131 1380000year 1500000year 15000...       price   \n",
       "1015     2  2 And And But But But But For He His I I In In...         NaN   \n",
       "1016     2  2 A A A A All And And And As As As As Because ...   sarachild   \n",
       "1017     1  A A A A A A A Against Ah Alice All Allies And ...         NaN   \n",
       "1018     1  A Another Association Association Christmas Ch...  Hull House   \n",
       "1019     1  100 106 1101tionse 1896 1897 1c6 1st 43 A Aid ...  Hull House   \n",
       "1020     2  1 1972 8 April Home Womankind and girls is no ...        CWLU   \n",
       "1021     2  95 Adn And And And Answering At At Because Bei...        CWLU   \n",
       "1022     2  1 1970 1971 2 3 4 5 6 A A A A According Aug Br...        leon   \n",
       "\n",
       "     page_number                   article_title  \n",
       "0             70                             NaN  \n",
       "1             06                             NaN  \n",
       "2             21                             NaN  \n",
       "3             01                marriagequestion  \n",
       "4             01                             NaN  \n",
       "5             30                             NaN  \n",
       "6             14                             NaN  \n",
       "7             01  programforconsciousnessraising  \n",
       "8             11                             NaN  \n",
       "9             20                             NaN  \n",
       "10            12                             NaN  \n",
       "11            06                             NaN  \n",
       "12            16                             NaN  \n",
       "13            08                             NaN  \n",
       "14            06                             NaN  \n",
       "15            08                             NaN  \n",
       "16            13                             NaN  \n",
       "17            05                             NaN  \n",
       "18            03                  mensliberation  \n",
       "19            03     workingconsciousnessraising  \n",
       "20            25                             NaN  \n",
       "21            01                whatwereallywant  \n",
       "22            03                             NaN  \n",
       "23            61                             NaN  \n",
       "24            04                             NaN  \n",
       "25            15                             NaN  \n",
       "26            02                conservatismofms  \n",
       "27            04                   psychologique  \n",
       "28            60                             NaN  \n",
       "29            43                             NaN  \n",
       "...          ...                             ...  \n",
       "993           08                             NaN  \n",
       "994           47                             NaN  \n",
       "995           10                             NaN  \n",
       "996           07                             NaN  \n",
       "997           28                             NaN  \n",
       "998           17                             NaN  \n",
       "999           13                             NaN  \n",
       "1000          01                   sexroletheory  \n",
       "1001          05                 keepingwomenout  \n",
       "1002          12                             NaN  \n",
       "1003          43                             NaN  \n",
       "1004          08                             NaN  \n",
       "1005          05                  powerofhistory  \n",
       "1006          03                             NaN  \n",
       "1007          03                     dirtytricks  \n",
       "1008          11                             NaN  \n",
       "1009          27                  powerofhistory  \n",
       "1010          22                             NaN  \n",
       "1011          18                             NaN  \n",
       "1012          06                             NaN  \n",
       "1013          01                             NaN  \n",
       "1014          11                 keepingwomenout  \n",
       "1015          18                             NaN  \n",
       "1016          13                  powerofhistory  \n",
       "1017          09                             NaN  \n",
       "1018          36                             NaN  \n",
       "1019          22                             NaN  \n",
       "1020          01                             NaN  \n",
       "1021          14                             NaN  \n",
       "1022          03                conditioningline  \n",
       "\n",
       "[1023 rows x 13 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Read in our dataframe to extract text\n",
    "df = pandas.read_csv(\"../data/comparativewomensmovement_dataset.csv\", sep='\\t', index_col=0, encoding='utf-8')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#concatenate the documents from each organization together, creaing four strings\n",
    "\n",
    "redstockings = df[df['org']=='redstockings']\n",
    "redstockings_string = ' '.join(str(s) for s in redstockings['text_string'].tolist())\n",
    "cwlu = df[df['org']=='cwlu']\n",
    "cwlu_string = ' '.join(str(s) for s in cwlu['text_string'].tolist())\n",
    "heterodoxy = df[df['org']=='heterodoxy']\n",
    "heterodoxy_string = ' '.join(str(s) for s in heterodoxy['text_string'].tolist())\n",
    "hullhouse = df[df['org']=='hullhouse']\n",
    "hullhouse_string = ' '.join(str(s) for s in hullhouse['text_string'].tolist())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='spec'></a>\n",
    "## Specificity Score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Calculate specificity score for each noun and verb in each string\n",
    "#Creates a list with word and specificity score for each string\n",
    "\n",
    "kant_specificity = specificty(kant_string)\n",
    "wiki_specificity = specificty(wiki_string)\n",
    "redstockings_specificity = specificty(redstockings_string)\n",
    "cwlu_specificity = specificty(cwlu_string)\n",
    "heterodoxy_specificity = specificty(heterodoxy_string)\n",
    "hullhouse_specificity = specificty(hullhouse_string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#extract just the specificity score from each list\n",
    "kant_specificity_array = list(int(x[1]) for x in kant_specificity)\n",
    "wiki_specificity_array = list(int(x[1]) for x in wiki_specificity)\n",
    "cwlu_specificity_array = list(int(x[1]) for x in cwlu_specificity)\n",
    "heterodoxy_specificity_array = list(int(x[1]) for x in heterodoxy_specificity)\n",
    "hh_specificity_array = list(int(x[1]) for x in hullhouse_specificity)\n",
    "red_specificity_array = list(int(x[1]) for x in redstockings_specificity)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ksreEhY0SHBpjjBnB9Otm7iCXZqQxkAkLjTHN08w6KAe5NCOKMoJc\nGmM6p18Tn4Nc9s748ZOQ1PJmRiaSNpR0g6RbJd2Rs1PbI9aYXuhkHdQM4HhJ9wBbsnaQy61zkMvP\n5HpExCKgFuRyDjnIZX5PVQty+SeSI8WQCHLZfvZPMxKJiOeAvSNiN1KOtQMk7YE9Yo1piIPFdkAn\nQV8dLHboMBDBYiVtAvyOlE36V8D4iFgjaU9gZkQcIOnKvH9DNpc/GhHbSJoBRESclvv6DXAy6Ys1\nMyIOyOVr1Sucu1JyVKTToK3dalvV+1kl2pEjR5IwZhDJC95vBZYBvwX+DKywR6wx62IFZcwgEhFr\nsolvAmkN4M6NquW/rXrE9lZuzJDE0cyN6QIR8ZSka4E9gS0G2yPWyzXMQFPGcg2/g+oAv4MaGZT1\nDkrS1sCqiFgpaWNgLnAqyev1PyPiUknfB26LiLMlHQ28LiKOlnQo8N6IODQ7SVwI7EEy4f0WeBXJ\nInI3sA/wKMlL9rB6p6OqyVERv4MavjhhoTHV5mXA+dnbbhRwaUTMkXQnTvtuzDp4BtUBnkGNDAbC\ni6+bVE2OingGNXyxF58xxphhQ78KyqvfjTHGdINmQh159bsxxphBpykTX0Q8m3c3JDlWBLA3zgdl\njDFmgGg2YaFXvxtjjBlUmnIzz4poN0mbAz+j3NXvzgdlKoXzQRlTDVpaB9Xt1e/gfFBm4HE+KGOq\nQTNefFtLGpP3NwbeRVogOOLzQRljjBk4mplBefW7McaYQceRJDrAkSRGBo4kMXg4ksTwxZEkjDHG\nDBusoIwZJCRNkHS1pEU5Ksunc/lYSfNyVJa5tXe++dh3c/SVhZJ2LZRPz5FX7pY0rVC+u6Tb87Ez\nB/cKjSkXKyhjBo/VwPER8VrgzcAxOWrKDOCqHJXlauBEAEkHADvkqCwfA87O5WOBLwFvIqXcmFlQ\nat8HjoqInYCdJO0/aFdnTMlYQRkzSETEsohYmPefBu4kLasoRl85nxcjqRwMzMr1bwDGSBpHCgs2\nLyJWRsQKkoPRVEnjgc0i4sbcfhYvRngxZshhBWVMF5A0iRTb8npgXET0QFJiwDa5Wm9RVvqKyrK0\nQX1jhiROWGjMICNpU1KcymMj4mlJvbmA1Xs81VzNWo3Wsg6OyGIGGqd87zJ2Mx8ZlOlmntPS/Ar4\nTUR8J5fdCUyJiJ5sppsfETtLOjvvX5rr3QXsRQrUPCUiPp7LzyYtnL+21jaXHwrsFRGfqBtDpeSo\niN3Mhy92Mzem+pwLLKopp8wVwOF5/3DWjsoyDUDSnqQAzT3AXGBfSWOyw8S+wNxsHnxK0mSlX/pp\nhb6MGXI0E+rIrrHGlICktwIfBt6plAD0FklTSbnV9pV0N7APcCpARMwBFku6D/gBcHQuXw58BVgA\n3ACckp0lyHXOAe4hpbG5ctAu0JiS6dfEl00O4yNiYbad30zyLjoCeCIiTs9ZcMdGxIzsGvvJiHh3\nTmz4nYjYMz/pLQB2J82nbwZ2j4iVkm4APhURN0qak9vMbTCWSpkmbOIbGTiSxOBhE9/wZUBMfHaN\nNcYY0w1a8uLryzVWkl1jjRkGLF68mK985Ru0Oyn47GePYZdddil3UGZE0rSCqoJrLNg91gw8Iz1h\n4a9//WsuuOBPrF79wXZaM3Hi5SNMQW2YTZOtM27cRJYte6Dc4QwjmlJQ2TV2NnBBRNS8gnokjSu4\nxj6Wy3tLTLgUmFJXPr+P+g1xwkIz0DhhIay33utZvfroNlo+1n+VYcdztPv+qqdn2LzaHBCadTO3\na6wxxphBpd8ZVME19g5Jt5IeFU4iucZeJulIYAk5u25OZnhgdo19huTtR077XnONDdZ1jf0xsBEw\nx66xxhhj+lVQEfFfwHq9HH5XL20+2Uv5j0mKqL78ZuD1/Y3FGGPMyGHYxOJ7xzsO5Oabb2i53ejR\no7n22rnsuuuu/Vc2xhgzaAwbBXXbbbfy7LO/A8a31G6zzT7K4sWLraCMMaZiDBsFldgS2KqlFtKG\nAzMUY4wxHeFgscYYYyqJFZQxg4SkcyT1SLq9UOagy8b0ghXUkCKtWG9nGz9+UrcHb+A8UkzKIjOA\nqyLi1cDVwIkAOejyDhHxKuBjwNm5fCzwJeBNwB7AzIJS+z5wVETsBOwkqf5cxgwprKCGFLUV661v\nPT0PdmPApkBE/AFYXlfsoMvG9EIz+aBsljBm4NimGHQZcNBlYzLNePGdB/wf8tNcpmaWqOWCOhGY\nUTRL5FxQZwN7FswSL+SCkvSLiFjJi2aJGyXNkbR/o1xQplPaC2jpYJZdw0GXzZCmjKDLzUSS+IOk\niXXFBwN75f3zSUFfZ1Bnlshx98YBe5PNEgCSamaJa2lslrCCKp32Alo6mOWA46DLZlhSRtDldt9B\n2SxhTHuItWc7DrpsTC+UvVB3QM0SYNOEGXgGKh+UpItIs5+tJC0BZgKnApcPp6DL3/zm90ZkihJT\nPu0qqK6YJcCmCTPwDFQ+qIj4UC+HhlXQ5WeeeYJ28yM1fmY1I5VmTXw2SxhjjBlUmnEzvwj4b9LC\nvyWSjiCZJfaVdDewT/5MRMwBFmezxA9IJgciYjlQM0vcwLpmiXOAe4B7u2GWOPLIo9ta/GqMMWbg\naMaLb9ibJVasWEZ7JgkrKWOMGSgcScIYY0wlsYIyxhhTSaygjDHGVBIrKGOMMZXECsoYY0wlsYIy\nxhhTSaygjDHGVBIrKGOMMZWkMgpK0lRJd+XEhSd0ezytc023BzBkGYjArCOZwZOlayrSR9X6KaOP\ncuSiLNnqloxWQkFJGgV8j5TOehfgMEmv6e6oWuWabg9ggNiwrTBQ48dPavoMVlDlMbiydE1F+qha\nP6300bt87b333n3K2HrrvaRfOWzURyuy+cIVjWQFBUwmxeF7MCJWAZeQkh+arlNLdNja1tPzYFdG\nayxLQ4u+5GtmH8eCNWue7fN4b30MJdksOx9UuzRKdDi5lQ422GB9NttsGtJGLZ3473+/qaX6plla\nSzFfS2nhFPMd07Esrb/++ki/YvPN+/4h+9vf7majjW5eq+y55+7muedaOZsxvaOIdvO2lDgI6QPA\nfhHxr/nzR4A3RcSxdfW6P1gzIomIIREZuBlZshyZbtGqHFVlBrUU2K7wuWHiwqHyI2FMF+lXlixH\nZqhQlXdQNwE7SpooaQPgUFLyQ2NMa1iWzLChEjOoiHhe0ieBeSSleU5E3NnlYRkz5LAsmeFEJd5B\nGWOMMfVUxcTXJ1VfxCvpAUm3SbpV0o0VGM85knok3V4oGytpnqS7Jc2VNKZCY5spaamkW/I2tUtj\nmyDpakmLJN0h6dO5vBL3rgw6laXe7lEH4xmV/+dtmyEljZF0uaQ7Jf1J0h5t9HGcpD9Kul3Shdk8\n2ky7jmWtlz5Oz9ezUNJPJW3ezlgKxz4raY2kLdvpQ9Kn8vfmDkmntjMWSW+QdF3td1LSG/vrh4io\n9EZSovcBE4H1gYXAa7o9rrox3g+M7fY4CuN5G7ArcHuh7DTg83n/BODUCo1tJnB8Be7beGDXvL8p\ncDfwmqrcuxKur2NZ6u0edTCm44CfAFd00MePgSPy/mhg8xbbb5tleIP8+VJgWpNtO5a1Xvp4FzAq\n758KfL2dseTyCcCVwGJgyzbGMoVkMh6dP2/d5n2ZS/IwBTgAmN9fP0NhBjUUFh6KCs1GI+IPwPK6\n4oOB8/P++cB7B3VQmV7GBukedpWIWBYRC/P+08CdJOGuxL0rgY5lqZd79PJ2BiNpAnAg8KN22uc+\nNgPeHhHn5TGtjoin2uhqPeAlkkYDm9DAi7gRZchaoz4i4qqIWJM/Xk/6HrYzFoAzgM/1176PPj5B\nUrKrc53H2+xnDVCbTW4BPNxfP5X5Ue2DRgsP2xKIASSAuZJukvQv3R5ML2wTET2QfmSAl3Z5PPUc\nk80ZP6qCCU3SJNIT4PXAuIrfu2YpVZYK9+iGNruo/XB28iJ8e+BxSedlU+F/SNq4lQ4i4hHgW8AS\n0o/mioi4qoMxlS1rRwK/aaehpPcAD0XEHR2cfyfgHZKulzS/KdNcY44DvilpCXA6cGJ/DYaCgmr0\nZF01z463RMQbSU+Dx0h6W7cHNMQ4C9ghInYFlgHf7uZgJG0KzAaOzbOEqn3f2qU0WWpwj1pt/26g\nJ8/G1MvYmmE0sDvw7xGxO/AsMKPFsWxBmvVMJJn7NpX0oTbHUyqSvgCsioiL2mi7MfAFkgn9heI2\nhjEa2CIi9gQ+D1zWRh+QZmLHRsR2JGV1bn8NhoKCamoRbzfJT0lExF+An9FiaJlBokfSOABJ44HH\nujyeF4iIv0Q2TAM/BN7UrbFkE89s4IKI+EUuruy9a5FSZKmXe9QqbwUOknQ/cDGwt6RZbfSzlDRD\nWJA/zyYprFZ4F3B/RDwZEc8D/wm8pY2x1Cjl+yJpOumht11luQMwCbhN0mLS//tmSdu02M9DpHtC\nRNwErJG0VRvjmR4RP8/9zKaJ38mhoKAqvfBQ0ib5aRJJLwH2A/7Y3VEB6z6VXgEcnvenA+3+sJTB\nWmPLQlzj/XT3/p0LLIqI7xTKqnTvOqEsWWp0j1oiIk6KiO0iYvs8jqsjYlob/fQAD0naKRftAyxq\nsZslwJ6SNpKk3Ecra8fKkLV6mZhKmq0cFBGtRDd8oZ+I+GNEjI+I7SPilSRlvltE9Kcw66/n56R7\nQr7P60fEE62MJfOwpL1yP/sA9/TbQ39eFFXYgKkkb6F7gRndHk/d2F5J8oa6FbijCuMDLiI9GT9H\nEr4jgLHAVfk+/pY0Za/K2GYBt+f7+HPSO59ujO2twPOF/+ct+bu3ZRXuXUnX2JEs9XaPOhzTXnTm\nxfcGkvJdSHrSH9NGHzNJSul2kmPD+k2261jWeunjXuDBfH9vAc5qZyx1x++nfy++RmMZDVyQf98W\nAHu1eV/ektvfClxHUpZ99uOFusYYYyrJUDDxGWOMGYFYQRljjKkkVlDGGGMqiRWUMcaYSmIFZYwx\nppJYQRljjKkkVlDGGGMqyf8DtwnaQKjiHOwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff97b2f6b70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#check for a normal distribution\n",
    "fig = plt.figure()\n",
    "ax1 = fig.add_subplot(221)   #top left\n",
    "ax2 = fig.add_subplot(222)   #top right\n",
    "ax3 = fig.add_subplot(223)   #bottom left\n",
    "ax4 = fig.add_subplot(224)   #bottom right\n",
    "\n",
    "ax1.hist(heterodoxy_specificity_array, bins=10)\n",
    "ax1.set_title(\"Heterodoxy\")\n",
    "ax2.hist(hh_specificity_array, bins = 10)\n",
    "ax2.set_title(\"Hull House\")\n",
    "ax3.hist(red_specificity_array, bins = 10)\n",
    "ax3.set_title(\"Redstockings\")\n",
    "ax4.hist(cwlu_specificity_array, bins = 10)\n",
    "ax4.set_title(\"CWLU\")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compare the Distributions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Specificity Score for Kant\n",
      "6.38739472969\n",
      "Mean Specificity Score for Wikipedia entry on Germany\n",
      "6.88140429227\n",
      "Mean Specificity Score for Heterodoxy\n",
      "6.6181868394\n",
      "Mean Specificity Score for Hull House\n",
      "6.73878070106\n",
      "Mean Specificity Score for Redstockings\n",
      "6.5018215975\n",
      "Mean Specificity Score for CWLU\n",
      "6.70855326471\n"
     ]
    }
   ],
   "source": [
    "#print descriptive stats\n",
    "\n",
    "print(\"Mean Specificity Score for Kant\")\n",
    "print(np.mean(kant_specificity_array))\n",
    "print(\"Mean Specificity Score for Wikipedia entry on Germany\")\n",
    "print(np.mean(wiki_specificity_array))\n",
    "print(\"Mean Specificity Score for Heterodoxy\")\n",
    "print(np.mean(heterodoxy_specificity_array))\n",
    "print(\"Mean Specificity Score for Hull House\")\n",
    "print(np.mean(hh_specificity_array))\n",
    "print(\"Mean Specificity Score for Redstockings\")\n",
    "print(np.mean(red_specificity_array))\n",
    "print(\"Mean Specificity Score for CWLU\")\n",
    "print(np.mean(cwlu_specificity_array))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#create an array for each city, and an array for each wave, for comparrison\n",
    "newyork_specificity_array = red_specificity_array + heterodoxy_specificity_array\n",
    "chicago_specificity_array = cwlu_specificity_array + hh_specificity_array\n",
    "\n",
    "firstwave_specificity_array = hh_specificity_array + heterodoxy_specificity_array\n",
    "secondwave_specificity_array = cwlu_specificity_array + red_specificity_array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.02905938603402421"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#compare percent difference on the specificity scale (1:18) for the test arrays\n",
    "(np.mean(wiki_specificity_array) - np.mean(kant_specificity_array)) / (max(wiki_specificity_array) - min(kant_specificity_array))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.011194438596294516"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#compare percent difference on the specificity scale (1:18) for the city arrays\n",
    "(np.mean(chicago_specificity_array) - np.mean(newyork_specificity_array)) / (max(chicago_specificity_array) - min(newyork_specificity_array))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0046830110323425097"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#compare percent difference on the specificity scale (1:18) for the wave arrays\n",
    "#note this difference is much smaller than the city-based difference\n",
    "(np.mean(firstwave_specificity_array) - np.mean(secondwave_specificity_array)) / (max(firstwave_specificity_array) - min(secondwave_specificity_array))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ttest_indResult(statistic=24.568635698492429, pvalue=3.3929628420398261e-133)\n",
      "Ttest_indResult(statistic=8.858902043752753, pvalue=8.1108293299567897e-19)\n"
     ]
    }
   ],
   "source": [
    "#calculate ttest statistics on city and wave arrays\n",
    "#note the statistic is much smaller on the wave-based arrays compared to the city-based arrays\n",
    "print(scipy.stats.ttest_ind(chicago_specificity_array, newyork_specificity_array))\n",
    "print(scipy.stats.ttest_ind(firstwave_specificity_array, secondwave_specificity_array))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='concrete'></a>\n",
    "## Concreteness Score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Read in the dictionary created by Brysbaert et al.\n",
    "dict_df = pandas.read_excel(\"../input_data/Concreteness_ratings_Brysbaert_et_al_BRM.xlsx\",sheetname=\"Sheet1\")\n",
    "dict_df = dict_df[dict_df['Bigram']==0]\n",
    "word_dict = dict_df.set_index(\"Word\")['Conc.M'].to_dict()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Calculate concreteness score for each noun and verb in each string\n",
    "#Creates a list of tuples, with word and concreteness score for each string\n",
    "\n",
    "kant_concrete = concrete(kant_string, word_dict)\n",
    "wiki_concrete = concrete(wiki_string, word_dict)\n",
    "redstockings_concrete = concrete(redstockings_string, word_dict)\n",
    "cwlu_concrete = concrete(cwlu_string, word_dict)\n",
    "heterodoxy_concrete = concrete(heterodoxy_string, word_dict)\n",
    "hullhouse_concrete = concrete(hullhouse_string, word_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#extract just the concreteness score from each list\n",
    "kant_concrete_array = list(int(x[1]) for x in kant_concrete)\n",
    "wiki_concrete_array = list(int(x[1]) for x in wiki_concrete)\n",
    "cwlu_concrete_array = list(int(x[1]) for x in cwlu_concrete)\n",
    "heterodoxy_concrete_array = list(int(x[1]) for x in heterodoxy_concrete)\n",
    "hh_concrete_array = list(int(x[1]) for x in hullhouse_concrete)\n",
    "red_concrete_array = list(int(x[1]) for x in redstockings_concrete)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Compare the Distributions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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GJzeZ8BIAM5sBPC/pGYKA5ZkxfQ3wfcJIvrnApDhYwnE6G1MIg4KSTADuiQt83ktQMyeO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\ncRwnk/x//+sGM0S8PWUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff970f6e400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#check for a normal distribution\n",
    "fig2 = plt.figure()\n",
    "ax1 = fig2.add_subplot(221)   #top left\n",
    "ax2 = fig2.add_subplot(222)   #top right\n",
    "ax3 = fig2.add_subplot(223)   #bottom left\n",
    "ax4 = fig2.add_subplot(224)   #bottom right\n",
    "\n",
    "ax1.hist(heterodoxy_concrete_array, bins=5)\n",
    "ax1.set_title(\"Heterodoxy\")\n",
    "ax2.hist(hh_concrete_array, bins = 5)\n",
    "ax2.set_title(\"Hull House\")\n",
    "ax3.hist(red_concrete_array, bins = 5)\n",
    "ax3.set_title(\"Redstockings\")\n",
    "ax4.hist(cwlu_concrete_array, bins = 5)\n",
    "ax4.set_title(\"CWLU\")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Concreteness Score for Kant\n",
      "1.89239482201\n",
      "Mean Concreteness Score for Wikipedia entry on Germany\n",
      "2.5470307759\n",
      "Mean Concreteness Score for Heterodoxy\n",
      "2.41836123207\n",
      "Mean Concreteness Score for Hull House\n",
      "2.66201702854\n",
      "Mean Concreteness Score for Redstockings\n",
      "2.29927131355\n",
      "Mean Concreteness Score for CWLU\n",
      "2.54317090307\n"
     ]
    }
   ],
   "source": [
    "#print descriptive stats\n",
    "\n",
    "print(\"Mean Concreteness Score for Kant\")\n",
    "print(np.mean(kant_concrete_array))\n",
    "print(\"Mean Concreteness Score for Wikipedia entry on Germany\")\n",
    "print(np.mean(wiki_concrete_array))\n",
    "print(\"Mean Concreteness Score for Heterodoxy\")\n",
    "print(np.mean(heterodoxy_concrete_array))\n",
    "print(\"Mean Concreteness Score for Hull House\")\n",
    "print(np.mean(hh_concrete_array))\n",
    "print(\"Mean Concreteness Score for Redstockings\")\n",
    "print(np.mean(red_concrete_array))\n",
    "print(\"Mean Concreteness Score for CWLU\")\n",
    "print(np.mean(cwlu_concrete_array))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#create one array for each city\n",
    "newyork_concrete_array = heterodoxy_concrete_array + red_concrete_array\n",
    "chicago_concrete_array = hh_concrete_array + cwlu_concrete_array\n",
    "\n",
    "#create one array for each wave\n",
    "firstwave_concrete_array = heterodoxy_concrete_array + hh_concrete_array\n",
    "secondwave_concrete_array = red_concrete_array + cwlu_concrete_array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.16365898847324101"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#compare percent difference on the concreteness scale (1:5) for the test arrays\n",
    "(np.mean(wiki_concrete_array) - np.mean(kant_concrete_array)) / (5-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.062775860855568189"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#compare percent difference on the concreteness scale (1:5) for the city-based arrays\n",
    "(np.mean(chicago_concrete_array) - np.mean(newyork_concrete_array)) / (5-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.034749901018524931"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#compare percent difference on the concreteness scale (1:5) for the wave-based arrays\n",
    "#notice this percent difference is around half as much as the city-based differernce\n",
    "(np.mean(firstwave_concrete_array) - np.mean(secondwave_concrete_array)) / (5-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ttest_indResult(statistic=-65.289536584554682, pvalue=0.0)\n",
      "Ttest_indResult(statistic=30.944453326355294, pvalue=7.2414699433184674e-210)\n"
     ]
    }
   ],
   "source": [
    "#calculate ttest statistics on the city- and wave-based arrays\n",
    "#note the statistic is more than twice as large for the New York/Chicago comparison versus the first wave/second wave comparison\n",
    "print(scipy.stats.ttest_ind(newyork_concrete_array, chicago_concrete_array))\n",
    "print(scipy.stats.ttest_ind(firstwave_concrete_array, secondwave_concrete_array))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='ner'></a>\n",
    "# Analysis 2: Count Organizations and People Mentioned using NER"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The below code counts the number of persons and organizations mentioned, and compares across organizations.\n",
    "\n",
    "**Note:** Because the published data is sorted, and not the full text, the code below will not reproduce the actual named entities counted. Instead, I will read in the saved named entities, count them, and print the output."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "#############################################################################################\n",
    "##Don't run this code to reproduce the named entities. It will not work on the sorted text.##\n",
    "#############################################################################################\n",
    "\n",
    "\n",
    "def extract_entities(text):\n",
    "    #text = text.decode('ascii','ignore') #convert all characters to ascii\n",
    "    text  = re.sub('[\\x00-\\x1f]',\" \", text)\n",
    "    org_list = []\n",
    "    person_list = []\n",
    "\n",
    "    for sent in nltk.sent_tokenize(text):\n",
    "        chunked = nltk.ne_chunk(nltk.pos_tag(nltk.word_tokenize(sent)))\n",
    "        for n in chunked:\n",
    "            if isinstance(n, nltk.tree.Tree):\n",
    "                if n.label()==\"ORGANIZATION\":\n",
    "                    org_list.append(' '.join(c[0] for c in n.leaves()))\n",
    "                if n.label()==\"PERSON\":\n",
    "                    person_list.append(' '.join(c[0] for c in n.leaves()))\n",
    "    return org_list, person_list\n",
    "\n",
    "org_strings = [hullhouse_string, heterodoxy_string, cwlu_string, redstockings_string]\n",
    "\n",
    "\n",
    "for org in org_strings:\n",
    "    org_list, person_list = extract_entities(org)\n",
    "    myList = [org_list, person_list]\n",
    "    filename=\"../input_data/named_entities_%s.json\" % org\n",
    "    \n",
    "    ##Uncomment the line below to save the named entities as a JSON file\n",
    "    #json.dump( myList_cwlu, open( filename, \"w\", endoding = 'utf-8' ) )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "##################################################################\n",
    "##Count saved named entities to reproduce named entity analysis.##\n",
    "##################################################################\n",
    "\n",
    "myList_cwlu = json.load( open (\"../input_data/named_entities_cwlu.json\", \"r\", \n",
    "                              encoding='utf-8') )\n",
    "\n",
    "cwlu_orgs =  myList_cwlu[0]\n",
    "cwlu_person = myList_cwlu[1]\n",
    "\n",
    "\n",
    "myList_hh = json.load( open (\"../input_data/named_entities_hullhouse.json\", \"r\", \n",
    "                              encoding = 'utf-8') )\n",
    "\n",
    "hh_orgs =  myList_hh[0]\n",
    "hh_person = myList_hh[1]\n",
    "\n",
    "\n",
    "myList_red = json.load( open (\"../input_data/named_entities_redstockings.json\", \"r\"),\n",
    "                     encoding='utf-8')\n",
    "\n",
    "red_orgs =  myList_red[0]\n",
    "red_person = myList_red[1]\n",
    "\n",
    "\n",
    "myList_heterodoxy = json.load( open (\"../input_data/named_entities_heterodoxy.json\", \"r\"),\n",
    "                            encoding='utf-8')\n",
    "\n",
    "heterodoxy_orgs =  myList_heterodoxy[0]\n",
    "heterodoxy_person = myList_heterodoxy[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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/iYhXiyi7mZm1Uk1dg9oJ2Bno0eA6VGegfTErTzWvQnnvb2KZi4CLCqTfD2xa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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff981bfc978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plots the number of organizations and persons mentioned by each organization\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    " \n",
    "# data to plot\n",
    "n_groups = 4\n",
    "num_persons = (len(hh_person), len(heterodoxy_person), len(cwlu_person), len(red_person))\n",
    "num_orgs = (len(hh_orgs), len(heterodoxy_orgs), len(cwlu_orgs), len(red_orgs))\n",
    "\n",
    " \n",
    "# create plot\n",
    "fig, ax = plt.subplots()\n",
    "index = np.arange(n_groups)\n",
    "bar_width = 0.35\n",
    "opacity = 0.8\n",
    " \n",
    "counts1 = plt.bar(index, num_persons, bar_width,\n",
    "                 alpha=opacity,\n",
    "                 color='b',\n",
    "                 label='Persons')\n",
    " \n",
    "counts2 = plt.bar(index + bar_width, num_orgs, bar_width,\n",
    "                 alpha=opacity,\n",
    "                 color='g',\n",
    "                 label='Organizations')\n",
    " \n",
    "plt.xlabel('Organization')\n",
    "plt.ylabel('Count of Named Entities')\n",
    "plt.title('Count of Named Entities by Organization')\n",
    "plt.xticks(index + bar_width, ('Hull House', 'Heterodoxy', 'CWLU', 'Redstockings'))\n",
    "plt.legend(loc='upper left')\n",
    " \n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
